CryoFold: Ab-initio structure determination from electrondensity maps using molecular dynamics

Mrinal Shekhar, Genki Terashi, Chitrak Gupta, Gaspard Debussche, Nicholas J. Sisco, Jonathan Nguyen, James Zook, John Vant, Daipayan Sarkar, Petra Fromme, Wade D. Van Horn, Ken Dill, Daisuke Kihara, Emad Tajkhorshid, Alberto Perez, Abhishek Singharoy

Jul 08, 2019
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Received Date: 25th June 19

Cryo-EM is a powerful method for determining biomolecular structures. But, unlike Xray crystallography or solution-state NMR, which are data-rich, cryo-EM can be data-poor. Cryo-EMroutinely gives electron density information to about 3–5 A° and the resolution often 
varies across the structure. So, it has been challenging to develop an automated computer algorithm that converts the experimental density maps to complete molecular structures. We address this challenge with CryoFold, a computational method that finds the chain trace from the density maps using MAINMAST, then performs molecular dynamics simulations using 
ReMDFF, a resolution-exchange flexible fitting protocol, accelerated by MELD, which uses low-information data to broaden the relevant conformational searching of secondary and tertiary structures. We describe four successes of structure determinations, including for membrane proteins and large molecules. CryoFold handles input data that is heterogeneous, and even sparse. The software is automated, and is available to the public via a python-based graphical user interface.

Read in full at bioRxiv.


This is an abstract of a preprint hosted on an independent third party site. It has not been peer reviewed but is currently under consideration at Nature Communications.

Nature Communications

Nature Research, Springer Nature